Data Analyst IV - Medicare, Medicaid, ACA, Risk Adjustment, SQL, Python

PLEASE NOTE: Salary ranges are geographically based and the posted range reflects the Northen CA region. Lower salary ranges will apply for other labor markets outside of NCAL

Overview:

The Risk Adjustment Operational Analytics leadership is seeking a Data Analyst to scope, deploy, and report on projects supporting prospective and retrospective risk adjustment initiatives. This pivotal role will build foundational reporting and analytical frameworks used to identify and prioritize risk adjustment opportunities, and will develop clear, insightful visualizations of opportunities and outcomes that directly inform strategic decision-making and operational excellence. The ideal candidate brings extensive, hands-on analytical experience and a demonstrated track record of translating complex data into actionable business intelligence within a dynamic healthcare environment. This position offers a significant opportunity to contribute to the organization's continued success in risk adjustment.

This role requires advanced technical coding expertise (e.g., SQL, R, or similar, with Python strongly preferred) sufficient to independently design, build, and optimize complex analytical solutions, or equivalent experience with statistical modeling programs. Prior knowledge of or experience in risk adjustment is preferred, along with familiarity in machine learning, predictive analytics, data modeling, and data visualization.

Job Summary:

This individual contributor is primarily responsible for driving strategic data-informed decisions, gathering data and information on targeted variables in an established systematic fashion, and preparing data for analytic efforts. This position executes creative data analytic approaches leading to actionable outcomes, interprets data analyses, and develops analytical and/or statistical models enabling informed business decisions.

Essential Responsibilities:

• Practices self-development and promotes learning in others by proactively providing information, resources, advice, and expertise with coworkers and customers; building relationships with cross-functional stakeholders; influencing others through technical explanations and examples; adapting to competing demands and new responsibilities; listening and responding to, seeking, and addressing performance feedback; providing feedback to others; creating and executing plans to capitalize on strengths and develop weaknesses; supporting team collaboration; and adapting to and learning from change, difficulties, and feedback.
• Completes work assignments and supports business-specific projects by applying expertise in subject area; supporting the development of work plans to meet business priorities and deadlines; ensuring team follows all procedures and policies; coordinating resources to accomplish priorities and deadlines; collaborating cross-functionally to make effective business decisions; solving complex problems; escalating high priority issues or risks as appropriate; and recognizing and capitalizing on improvement opportunities.
• Interprets data analyses by applying findings to contextual settings; and developing insights, reports, and presentations telling a compelling story to stakeholders to enable and influence decision making; and providing context related to data interpretations and/or limitations as appropriate.
• Executes creative data analytic approaches leading to actionable outcomes by defining and calculating metrics to be analyzed; defining, calculating, and validating algorithms; and conducting analyses, including descriptive, correlational, inferential, and/or predictive statistics.
• Develops analytical and/or statistical models enabling informed business decisions by determining data and analytical requirements; creating models leading to actionable insights; and testing, refining, and validating models.
• Gathers data and information on targeted variables in an established systematic fashion by validating data sources; querying, merging, and extracting data across sources; completing routine data refresh and update; developing and/or delivering tools for electronic data collection; and providing user training, support, and documentation.
• Drives strategic data-informed decisions by consulting with clients to identify and clarify key business needs; developing outcomes and process measures; translating business requirements; determining data/information needs and data collection methods; developing analysis plans; measuring the impact of business decisions on clients, customers, and/or members; working with clients and staff to identify opportunities and methods to improve efficiencies with analysis; supporting and training end-users; and documenting processes and deliverables.
• Prepares data for analytic efforts by integrating and consolidating data; ensuring data quality and accuracy; profiling data inaccuracies and recommending process improvements or system changes to enhance overall quality of the data; and cleaning and creating final data set(s) for analysis.